Classification with class-independent quality information for biometric verification
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In this paper, several approaches that can be used to improve biometric authentication applications are proposed. The idea is inspired by the ensemble approach, i.e., the use of several classifiers to solve a problem. Compared to using only one classifier, ...
In this paper, several approaches that can be used to improve biometric authentication applications are proposed. The idea is inspired by the ensemble approach, i.e., the use of several classifiers to solve a problem. Compared to using only one classifier, ...
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Ensemble algorithms can improve the performance of a given learning algorithm through the combination of multiple base classifiers into an ensemble. In this paper, the idea of using an adaptive policy for training and combining the base classifiers is put ...
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We compare two classifier approaches, namely classifiers based on Multi Layer Perceptrons (MLPs) and Gaussian Mixture Models (GMMs), for use in a face verification system. The comparison is carried out in terms of performance, robustness and practicability ...
